A modern look at the relationship between sharpness and generalization [ICML 2023]
☆43Sep 11, 2023Updated 2 years ago
Alternatives and similar repositories for sharpness-vs-generalization
Users that are interested in sharpness-vs-generalization are comparing it to the libraries listed below
Sorting:
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆38Jun 14, 2022Updated 3 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30May 16, 2022Updated 3 years ago
- Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)☆28Dec 22, 2020Updated 5 years ago
- ☆13Jun 23, 2022Updated 3 years ago
- [NeurIPS 2022] "Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets" by Ruisi Cai*, Zhenyu Zh…☆21Oct 1, 2022Updated 3 years ago
- Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"☆21Dec 10, 2021Updated 4 years ago
- [NeurIPS'22] Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork. Haotao Wang, Junyuan Hong,…☆15Nov 27, 2023Updated 2 years ago
- ☆13Mar 22, 2023Updated 2 years ago
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆25Jul 25, 2024Updated last year
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆36Jul 3, 2021Updated 4 years ago
- A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturb…☆12Aug 5, 2020Updated 5 years ago
- ☆19Jun 10, 2024Updated last year
- A School for All Seasons on Trustworthy Machine Learning☆12Jun 30, 2021Updated 4 years ago
- Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]☆29Sep 22, 2023Updated 2 years ago
- ☆34Jan 25, 2024Updated 2 years ago
- Source code for "Neural Anisotropy Directions"☆16Nov 17, 2020Updated 5 years ago
- Why Do We Need Weight Decay in Modern Deep Learning? [NeurIPS 2024]☆70Sep 25, 2024Updated last year
- Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet☆32Aug 22, 2023Updated 2 years ago
- Code for the paper "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]☆21Apr 15, 2024Updated last year
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆49Dec 30, 2021Updated 4 years ago
- [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?☆29Mar 15, 2022Updated 3 years ago
- ☆46May 8, 2024Updated last year
- [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training☆32Jan 9, 2022Updated 4 years ago
- ☆19Jun 21, 2021Updated 4 years ago
- [CVPR 2024] This repository includes the official implementation our paper "Revisiting Adversarial Training at Scale"☆20Apr 21, 2024Updated last year
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆19Nov 30, 2022Updated 3 years ago
- ☆39Oct 21, 2022Updated 3 years ago
- Computing various measures and generalization bounds on convolutional and fully connected networks☆35Dec 13, 2018Updated 7 years ago
- ☆30Jun 19, 2023Updated 2 years ago
- Data for "Datamodels: Predicting Predictions with Training Data"☆97May 25, 2023Updated 2 years ago
- A Closer Look at Accuracy vs. Robustness☆88May 17, 2021Updated 4 years ago
- ☆52Jun 10, 2024Updated last year
- SGD with large step sizes learns sparse features [ICML 2023]☆33Apr 24, 2023Updated 2 years ago
- A united toolbox for running major robustness verification approaches for DNNs. [S&P 2023]☆90Mar 24, 2023Updated 2 years ago
- Understanding and Improving Fast Adversarial Training [NeurIPS 2020]☆96Sep 23, 2021Updated 4 years ago
- ☆10Oct 31, 2022Updated 3 years ago
- Github Repo for ICML 2022 paper: Communication-Efficient Adaptive Federated Learning☆10Nov 18, 2022Updated 3 years ago
- Distilling Model Failures as Directions in Latent Space☆47Feb 8, 2023Updated 3 years ago
- [ICML 2024] Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models☆157Feb 19, 2026Updated last week